Functional Analysis of Artificial Neural Network for Dataset Classification

Classification is one of the most active research and application areas of artificial neural networks (ANN). One of the difficulties in using ANN is to find the most suitable combination of training, learning and transfer function for classification of data sets with increasing number of features and classified sets. In this paper we have studied the effect of different combinations of functions while using artificial neural network as a classifier and analyzed the suitability of these functions for different kinds of datasets. The appropriateness of the proposed work has been determined on the basis of mean square error, rate of convergence, and accuracy of the classified dataset. Our inferences are based on the simulation results over the datasets used.

Thanatin : An emerging host defense antimicrobial peptide with multiple modes of action

Antimicrobial peptides (AMPs) possess great potential for combating drug-resistant bacteria. Thanatin is a pathogen-inducible single-disulfide-bond-containing β-hairpin AMP which was first isolated from the insect Podisus maculiventris. The 21-residue-long thanatin displays broad-spectrum activity against both Gram-negative and Gram-positive bacteria as well as against various species of fungi. Remarkably, thanatin was found to be highly potent in inhibiting the growth of bacteria and fungi at considerably low concentrations. Although thanatin was isolated around 25 years ago, only recently has there been a pronounced interest in understanding its mode of action and activity against drug-resistant bacteria. In this review, multiple modes of action of thanatin in killing bacteria and in vivo activity, therapeutic potential are discussed. This promising AMP requires further research for the development of novel molecules for the treatment of infections caused by drug resistant pathogens.Published versio

Prevalence of rotaviral diarrhoea in under-five hospitalized children in a tertiary care hospital of Eastern India

Background: To monitor the prevalence of rotaviral diarrhoea in under-5 children (U5C) as a retrospective study in a tertiary care hospital during 1 year. Methods: Suspected stool samples were diagnosed for rotavirus by an enzyme immunoassay kit. The same stool samples were diagnosed for the detection of any secondary bacterial infection through routine microbiological diagnosis. Results and conclusions: Of the total 265 stool samples, 123 were diagnosed positive with rotaviral infection, of which, 59 (50.86%) samples were from children in the age group of 0–12 months; further, 28 (41.79%), 17 (58.52%), 14 (35.71%) and 5 (46.41%) were from age groups, 13–24, 25–36, 37–48 and 49–60 months, respectively. Cases of secondary bacteremia were with Klebsiella sp., Enterobacter sp., Escherichia coli and Shigella sp. in the stool samples in age groups as given: 14 (0–12 month), 3 (13–24 month), 2 (37–48 month) and 1 (25–36 month). Of the total 123 rotaviral positive infants, 62 patients had fever and 100 patients had vomiting; while, 57, 47 and 10 patients had ‘mild’, ‘moderate’ and ‘severe’ dehydration, respectively. Further, 34 and 89 rotaviral positive children were with malnutrition and normal nutrition, respectively; while, 19, 89 and 15 patients were hospitalized for ⩽2, 3–6, and ⩾7 days, respectively. Data sets for ‘severity of dehydration’ and ‘days of hospitalization’ were statistically significant, with Kruskal–Wallis H-test, independently. Of 142 rotaviral negative patients, 27 with bacterial diarrhoea, 6 with parasitic infections, 20 with antibiotic intolerance and 31 with lactose intolerance were recorded

Association of meteorological parameters with intussusception in children aged under 2 years: results from a multisite bidirectional surveillance over 7 years in India

Objectives The study aimed to document the association between intussusception in Indian children and meteorological parameters and examine regional variations.Design A bidirectional (retrospective and prospective) surveillance between July 2010 and September 2017.Setting At 20 hospitals in India, retrospective case record review during July 2010 and March 2016 and prospective surveillance during April 2016 and September 2017 were performed.Participants 2161 children aged 2–24 months with first intussusception episode were included.Interventions The monthly mean meteorological parameters (temperature, sunshine, rainfall, humidity and wind speed) for the study sites were collected.Methods The association between monthly intussusception cases and meteorological parameters was examined at pooled, regional and site levels using Pearson (r) and Spearman’s rank-order (ρ) correlation, factorial analysis of variance, and Poisson regression or negative binomial regression analyses.Results The intussusception cases were highest in summer and lowest in autumn seasons. Pearson correlation analysis showed that temperature (r=0.056; p<0.05), wind speed (r=0.134; p<0.01) and humidity (r=0.075; p<0.01) were associated with monthly intussusception cases. Spearman’s rank-order correlation analysis found that temperature (ρ=0.049; p<0.05), wind speed (ρ=0.096; p<0.01) and sunshine (ρ=0.051; p<0.05) were associated with monthly intussusception cases. Poisson regression analysis resulted that monthly intussusception case was associated with rising temperature (North region, p<0.01 and East region, p<0.05), sunshine (North region, p<0.01), humidity (East region, p<0.01) and wind speed (East region, p<0.01). Factorial analysis of variance revealed a significant seasonal difference in intussusception cases for pooled level (p<0.05), 2–6 months age group (p<0.05) and North region (p<0.01). Significant differences in intussusception cases between summer and autumn seasons were observed for pooled (p<0.01), children aged 2–6 months (p<0.05) and 7–12 months (p<0.05).Conclusions Significant correlations between intussusception cases and temperature, humidity, and wind speed were observed at pooled and regional level in India. A peak in summer months was noted, which may be used for prediction, early detection and referral for appropriate management of intussusception